Update app.py

app.py

@@ -1,15 +1,11 @@
 import cv2
 import spaces
 import numpy as np
-import tensorflow as tf
 import gradio as gr
 import tempfile
 import os
 os.environ['CUDA_VISIBLE_DEVICES'] = "0"
 
-print(tf.config.list_physical_devices("GPU"))
-model = tf.keras.models.load_model('cnn.keras')
-
 # Function to preprocess each frame
 def preprocess_frame(frame):
     resized_frame = cv2.resize(frame, (224, 224))  # Adjust size based on your model's input shape
@@ -19,6 +15,9 @@ def preprocess_frame(frame):
 @spaces.GPU(duration=120)
 def predict_drowsiness(video_path):
     # Open the video file
+    import tensorflow as tf
+    print(tf.config.list_physical_devices("GPU"))
+    model = tf.keras.models.load_model('cnn.keras')
     cap = cv2.VideoCapture(video_path)
     frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
     frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))